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Record W2005209946 · doi:10.1002/cjce.5450820123

Isomérisation du <i>n</i>‐hexane sur des catalyseurs Ni‐WO<sub>x</sub>/Al<sub>2</sub>O<sub>3</sub>‐SiO<sub>2</sub>

2004· article· en· W2005209946 on OpenAlexvenueno aff
Miloud Guemini, Yacine Rezgui, Ahcene Bouchemma, Ammar M. Tighezza

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCatalysisNickelTungstenIsomerizationYield (engineering)SelectivityHexaneMaterials scienceChemistryAnalytical Chemistry (journal)Nuclear chemistryMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Isomerization of n ‐hexane into bi‐ and tri‐branched products was studied at atmospheric pressure on Ni‐WO x /Al 2 O 3 ‐SiO 2 catalysts. Two groups of catalysts (A and B) were prepared by using the sol‐gel method. The objective of the present study is the selection of the catalyst having the best isomer (bi‐ and tri‐branched) yield under optimum operating conditions (reaction temperature, reduction temperature, flow duration, etc.). The results show that the introduction of tungsten (group B) modifies siginificantly the catalyst activity and that the optimum nickel amount in these catalysts is 15 wt. %. When a steady flow is achieved (100 min), the catalyst containing 15 % nickel and 10 % tungsten exhibits the highest and largest selectivity at a reaction temperature of 250°C and a reduction temperature of 430°C.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.173
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2004
Admission routes1
Has abstractyes

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